Many public and private sector organisations work in an environment where complex calculations are required to determine entitlements and obligations of customers against an ever-changing base of policy rules. Such rules may be business rules, or implementation of the law. This is particularly true of government agencies administering tax, social security, social services, immigration or compensation, for example. In addition, private institutions such as banks and insurers rely on complex framework for investments or claims.
Previous systems run loop-based code to devise segments of data. Such an approach involves a great deal of input/output data, where complex calculations rely on a significant number of input factors. These systems are inefficient as loop-based code tests for outcomes of every possible data result, that is, calculate values at every possible data point, when only a small segment of data is of interest, or the result only changes at certain data points.
For example, where eligibility payments are dependent on a claimant's age, there may only be five or six significant dates, yet previous loop-based coding tests for eligibility on potentially tens of thousands of different dates. The actual dates of interest are not distinguishable, and must be extracted by some means.
The present invention advantageously provides an alternative to existing time-based programming and computation in a complex policy environment.